---
title: 'Research Intern at Vizzia'
canonical: 'https://feeny.ai/job/research-intern-vizzia-paris-mw596jkb019d'
type: 'job'
last_seen: '2026-11-12'
---

# Research Intern at Vizzia

- **Company:** Vizzia
- **Location:** Paris, France
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-11-10
- **Last confirmed live:** 2026-11-12
- **Apply:** https://jobs.ashbyhq.com/vizzia/e75448e8-dd7c-43b8-8048-dad84330c028

## Job description

Context Vizzia's cameras stay on the same streets for months and process video in the field, under strict compute and energy constraints. Two research questions come directly from that setup. How do you understand what changed in a scene over hours or days, when classic methods only compare two frames? And how do you use urban video to train models and deliver clips to local authorities, while protecting the people who appear in it without having anything to do with the event? 250+ local authorities already rely on Vizzia to keep their streets clean and safe. Each of these questions affects what our cameras can detect and how we handle the data behind it. We are opening two end-of-studies research internships in our R&D team, one per question. Same internship, same setup, two subjects. Each is built around a research question, a hypothesis to test, public benchmarks and long real-world Vizzia sequences, and is designed to support your master's thesis. The internship lasts 6 months, with the possibility of continuing as a CIFRE PhD.

## What You'll Do

1. Subject A: Modelling the long-term state of an urban scene

- Implement pixel-level baselines (background subtraction, learned change detection on image pairs) and low frame rate tracking, and quantify where they fail
- Design an object-centric scene memory: detect objects with open-vocabulary detectors (Grounding DINO, OWLv2), segment them (SAM 2), describe them with lighting-robust features (DINOv2) and their presence history, and assign each object a state updated over time: permanent, temporary, new, removed
- Target cases from Vizzia's field use: illegal dumping, abandoned luggage, vehicles parked for days, damaged or missing street furniture
- Characterise failure modes by observation rate, history length, day/night and weather, object shape and evolution (a pile of waste that grows, a tarp moving in the wind), scene density and occlusions
- Evaluate on events rather than frames: precision and recall of appearances and disappearances, detection delay, false alerts per camera per day, on PETS 2006, i-LIDS / AVSS 2007, ABODA, CDnet 2014 and Vizzia sequences

1. Subject B: Anonymising urban video while preserving its utility

- Build detect-then-blur baselines (RetinaFace, EgoBlur, Vizzia's in-house plate detector), measure missed detections first (small faces, night, motion blur), then quantify the recall gained by propagating anonymisation through tracking
- Compare generative replacement methods: DeepPrivacy2 full-body GAN, diffusion inpainting for faces, full-body diffusion and video regeneration from structural cues (pose, segmentation, depth), plus synthetic plates with known text
- Work on temporal consistency (one stable synthetic identity per track, no flicker) and on selective anonymisation for clips delivered to local authorities: everyone except the people involved in the event
- Measure protection (residual leaks per 1,000 frames, ArcFace and person re-ID attacks, OCR on anonymised plates) against utility (detection and tracking performance of models trained on raw vs anonymised video, event readability for an operator), within the frame of GDPR and the CNIL's 2022 position on augmented cameras
- Evaluate on MOT17, MOT20, Cityscapes, BDD100K and Vizzia sequences

1. Common to both subjects

- Start with a literature review, then build test sets from public benchmarks and long Vizzia sequences, part of which you will annotate during the internship
- Define the evaluation protocol and metrics before running the main experiments
- Deliver a model or pipeline evaluated on public and Vizzia data, a documented benchmark, clean code, integration recommendations and your master's thesis

## Who You Are

- Final-year student in an M2 or engineering school, specialised in computer vision, machine learning or applied mathematics
- Fluent in Python and PyTorch, and comfortable processing video streams
- For Subject A: knowledge of object detection, multi-object tracking or visual representation learning. For Subject B: knowledge of generative models (GAN, diffusion, inpainting), detection, tracking or re-identification, and an interest in personal data protection
- Technical English good enough to read and synthesize research papers
- Rigorous with experiments and able to move a research question forward on your own

At Vizzia, we care about precision, ownership and getting things done. We're looking for people who are genuinely interested in what public-sector work involves.

## Compensation & Benefits

🏡 Hybrid work 🏝 Mandatory internship agreement from your school (1 day off per month) 💻 MacBook ou PC 🍜 60% coverage of meal vouchers worth €9 per day worked 🚃 50% Navigo pass reimbursement 💼 Offices located in central Paris (9th arrondissement) ☀️ Annual offsite with the whole team and plenty of company events If you've read this far, you're probably very interested in the role and/or Vizzia. We'd like to hear from you even if you feel you don't check every box.

## About Vizzia

## Company Overview
- **One-liner**: Vizzia provides mobile surveillance devices and software that help European local authorities tackle illegal dumping, public safety issues, and anti-social behaviour while respecting privacy and GDPR.
- **Entity Type**: Private (Series B, raised ~$58.9M total)
- **Headquarters**: Paris, France (51 Rue de Turbigo, 75003)
- **Founded**: 2020
- **Founders**: Catherine De Proyart (CEO) and Alexandre Leboucher (CTPO)

## Core Business
- Primary industry: Public-sector technology / GovTech / Municipal enforcement
- Target customers: B2G – local authorities (towns, cities, councils) and their enforcement teams (municipal police, technical services)
- Mission: “Make cities and communities better places to live — cleaner, safer, easier to look for.”

## Products & Services
- **Vizzia Waste**: A hardware + software solution to detect and stop illegal dumping. Remotely deployed mobile devices capture incidents (GPS, timestamp, imagery) and streamline evidence collection, legal procedures, and fine issuance. Up to 90% reduction in fly-tipping reported.
- **Vizzia Safety**: Similar platform focused on public safety disturbances (anti-social behaviour, local safety issues). Helps municipalities spot offences, gather admissible evidence, and take action without intrusive surveillance.
- Both products are GDPR‑compliant, hosted in the EU, require no roadworks or fiber, and can be deployed “in days, not months.”

## Market Standing
- **Valuation**: Not publicly disclosed
- **Key Metrics**:
  - €1M+ in fines collected through the platform
  - 110,000+ incidents reported in the last 12 months
  - 200+ cities equipped across Europe (250+ per some sources)
- **Total Funding**: ~$58.9M (Series B of ~$35.4M raised in February 2026)
- **Notable Investors/Partners**: Headline, Base10 Partners, SISTAFUND, Made for All
- **Growth Signals**:
  - Headcount grew to 130+ (as of May 2026) with “strong growth ahead”
  - Expansion across Europe: from rural towns to large councils
  - Series B raised only 4 months ago indicates strong investor confidence and cash runway

## Competitive Advantages
- **Speed & Simplicity**: No construction or fiber required; devices are easily moved and deployed remotely.
- **GDPR‑first Privacy**: Data hosted in the EU and designed from the start to protect civil liberties, a critical trust factor for public-sector clients.
- **Legal‑Ready Output**: Each detection includes the forensic metadata (GPS, timestamp, imagery) needed to issue fines and prosecute cases – reducing administrative burden on enforcement teams.
- **Tangible Resident‑Visible Results**: Metrics like “90% decrease in fly-tipping” help councils demonstrate impact to residents.

## Strategic Focus
- Continue scaling across Europe’s 200+ already‑equipped municipalities and entering new countries.
- Deepen the product suite to cover more municipal pain points (cleanliness, safety) while staying “simple and results‑oriented.”
- Invest in the platform’s automation to further reduce manual paperwork for enforcement teams.

## Why Work Here
- **Culture**: The company looks for “owners, not executors” – people who move fast, push for outcomes, and care about citizens behind the product. Emphasis on inventing, simplifying, and amplifying the team rather than optimizing one’s own lane.
- **Team Size**: ~130 people with a “strong growth ahead” – opportunity to have outsized impact as the company scales.
- **Location & Flexibility**: Headquarters in central Paris (51 Rue de Turbigo). Remote/hybrid policy not specified, but the team is European and product‑focused.
- **Mission‑Driven**: Directly improving quality of life in communities – a concrete, visible impact that appeals to people who want their work to matter beyond the bottom line.

## Sources
1. [vizzia.com](https://www.vizzia.com/en)
2. [welcometothejungle.com](https://www.welcometothejungle.com/en/companies/vizzia)
3. [cbinsights.com](https://www.cbinsights.com/company/vizzia)
4. [tracxn.com](https://tracxn.com/d/companies/vizzia/__9dxWmXmMGz4rW8rtQEmFKmEV7R-xUg-nOdVWW6S8RaE)

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